Machine learning has become a hugely popular topic in the last years. Everybody is talking about it and it has shown to be very helpful for different purposes. However, which are the potential benefits of machine learning applied to research and how can machine learning methods get to be an integral part of a software project? This workshop will provide an answer to these questions.
In particular, you will get an overview of good practices that will help you start your Open Source Software project. You will get some insight on helpful tools for unit testing, package management, continuous integration and containerisation.
On the second day you will get familiar with the basics of machine learning and some advice on how to use different support libraries to build your own software project. The theory on the different types of learning will be mixed with hands-on exercises using Jupyter notebooks, which run on the systems at SURFsara.
Who:
The course is aimed at graduate students and other researchers, as well as anybody who would like to learn the basics for the development of open-source software and cloud-based services.
Where:
SURFsara. Science Park 140, 1098 XG Amsterdam. Room VK1/VK2.
Get directions with
OpenStreetMap
or
Google Maps.
Requirements: Participants must bring a laptop with a
Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).
Participants should have at least a basic level of programming experience (preferably in Python).
Main concepts in artificial intelligence and machine learning
Types of learning and available libraries
Hands-on exercises on modelization and optimization
Data competition: challenge your knowledge!
(Optional) Bring your own problem and get help onsite
Schedule
Day 1
09:00 - 10:30
Using OSS for research
10:30 - 10:45
Morning break
10:45 - 12:00
Packaging software
12:00 - 13:00
Lunch break
13:00 - 14:30
Unit testing and continuous integration
14:30 - 14:45
Afternoon break
14:45 - 17:00
Containers
Day 2
09:00 - 10:30
Introduction to artificial intelligence and machine learning
10:30 - 10:45
Morning break
10:45 - 12:00
Practical session - data handling, management and visualization
12:00 - 13:00
Lunch break
13:00 - 14:30
Practical session - data modeling
14:30 - 14:45
Afternoon break
14:45 - 17:00
Data challenge with competition (optional: bring your own problem!)
The catering for the lunch and morning/evening breaks will be provided by the organization.
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
Setup
To participate in this
SURF/eScience
workshop,
you will need access to the software described below.
In addition, you will need an up-to-date web browser.
The Bash Shell
Bash is a commonly-used shell that gives you the power to do simple
tasks more quickly.
Click on "Next" four times (two times if you've previously
installed Git). You don't need to change anything
in the Information, location, components, and start menu screens.
Select "Use the nano editor by default" and click on "Next".
Keep "Use Git from the Windows Command Prompt" selected and click on "Next".
If you forgot to do this programs that you need for the workshop will not work properly.
If this happens rerun the installer and select the appropriate option.
Click on "Next".
Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
Select "Use Windows' default console window" and click on "Next".
Click on "Install".
Click on "Finish".
If your "HOME" environment variable is not set (or you don't know what this is):
Open command prompt (Open Start Menu then type cmd and press [Enter])
Type the following line into the command prompt window exactly as shown:
setx HOME "%USERPROFILE%"
Press [Enter], you should see SUCCESS: Specified value was saved.
Quit command prompt by typing exit then pressing [Enter]
This will provide you with both Git and Bash in the Git Bash program.
The default shell in all versions of macOS is Bash, so no
need to install anything. You access Bash from the Terminal
(found in
/Applications/Utilities).
See the Git installation video tutorial
for an example on how to open the Terminal.
You may want to keep
Terminal in your dock for this workshop.
The default shell is usually Bash, but if your
machine is set up differently you can run it by opening a
terminal and typing bash. There is no need to
install anything.
Git
Git is a version control system that lets you track who made changes
to what when and has options for easily updating a shared or public
version of your code
on github.com. You will need a
supported
web browser.
You will need an account at github.com
for parts of the Git lesson. Basic GitHub accounts are free. We encourage
you to create a GitHub account if you don't have one already.
Please consider what personal information you'd like to reveal. For
example, you may want to review these
instructions
for keeping your email address private provided at GitHub.
For OS X 10.9 and higher, install Git for Mac
by downloading and running the most recent "mavericks" installer from
this list.
Because this installer is not signed by the developer, you may have to
right click (control click) on the .pkg file, click Open, and click
Open on the pop up window.
After installing Git, there will not be anything in your /Applications folder,
as Git is a command line program.
For older versions of OS X (10.5-10.8) use the
most recent available installer labelled "snow-leopard"
available here.
If Git is not already available on your machine you can try to
install it via your distro's package manager. For Debian/Ubuntu run
sudo apt-get install git and for Fedora run
sudo dnf install git.
Text Editor
When you're writing code, it's nice to have a text editor that is
optimized for writing code, with features like automatic
color-coding of key words. The default text editor on macOS and
Linux is usually set to Vim, which is not famous for being
intuitive. If you accidentally find yourself stuck in it, hit
the Esc key, followed by :+Q+!
(colon, lower-case 'q', exclamation mark), then hitting Return to
return to the shell.
nano is a basic editor and the default that instructors use in the workshop.
It is installed along with Git.
Others editors that you can use are
Notepad++ or
Sublime Text.
Be aware that you must
add its installation directory to your system path.
Please ask your instructor to help you do this.
nano is a basic editor and the default that instructors use in the workshop.
See the Git installation video tutorial
for an example on how to open nano.
It should be pre-installed.
Python is a popular language for
research computing, and great for general-purpose programming as
well. Installing all of its research packages individually can be
a bit difficult, so we recommend
Anaconda,
an all-in-one installer.
Regardless of how you choose to install it,
please make sure you install Python version 3.x
(e.g., 3.6 is fine).
We will teach Python using the Jupyter notebook,
a programming environment that runs in a web browser. For this to work you will need a reasonably
up-to-date browser. The current versions of the Chrome, Safari and
Firefox browsers are all
supported
(some older browsers, including Internet Explorer version 9
and below, are not).
Download the Python 3 installer for Linux.
(The installation requires using the shell. If you aren't
comfortable doing the installation yourself
stop here and request help at the workshop.)
Open a terminal window.
Type
bash Anaconda3-
and then press
Tab. The name of the file you just downloaded should
appear. If it does not, navigate to the folder where you
downloaded the file, for example with:
cd Downloads
Then, try again.
Press Return. You will follow the text-only prompts. To move through
the text, press Spacebar. Type yes and
press enter to approve the license. Press enter to approve the
default location for the files. Type yes and
press enter to prepend Anaconda to your PATH
(this makes the Anaconda distribution the default Python).